Applicability of a bioelectronic cardiac monitoring ...

Journal of Marine Systems 171 (2017) 151–158

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Journal of Marine Systems journal homepage: www.elsevier.com/locate/jmarsys

Applicability of a bioelectronic cardiac monitoring system for the detection of biological effects of pollution in bioindicator species in the Gulf of Finland Sergey V. Kholodkevich a,b, Tatiana V. Kuznetsova a, Andrey N. Sharov a,⁎, Anton S. Kurakin a, Urmas Lips c, Natalia Kolesova c, Kari K. Lehtonen d a

Saint-Petersburg Scientific Research Center for Ecological Safety, Russian Academy of Sciences, Korpusnaya 18, St Petersburg 197110, Russia Saint-Petersburg State University, 7-9 Universitetskaya nab., St Petersburg 199034, Russia c Marine Systems Institute, Tallinn University of Technology, Akadeemia tee 15a, 12618 Tallinn, Estonia d Finnish Environment Institute, Hakuninmaantie 6, FI-00430 Helsinki, Finland b

a r t i c l e

i n f o

Article history: Received 14 April 2016 Received in revised form 15 December 2016 Accepted 19 December 2016 Available online 23 December 2016 Keywords: Gulf of Finland Biomonitoring Bioelectronic systems Heart rate recovery cardiac activity Bivalve mollusks Pollution

a b s t r a c t Field testing of an innovative technology based on a bioelectronic cardiac monitoring system was carried out in the Gulf of Finland (Baltic Sea). The study shows that the bioelectronic system is suitable for the selected bivalve mollusks Mytilus trossulus, Macoma balthica and Anodonta anatina. Specimens taken from reference sites demonstrated a heart rate recovery time of b 60 min after testing with changed salinity load, while those collected from sites characterized by high anthropogenic pressure demonstrated a prolonged recovery time of up to 110–360 min. These results make possible a discrimination of the study sites based on the assessment of physiological adaptive capacities of inhabiting species. In addition, the approach of measuring heart rate characteristics in M. balthica transplanted in cages to specific target areas was successfully used to evaluate the decline in the adaptive potential of mollusks exposed at polluted sites. Application of the novel system is a useful tool for the biomonitoring of freshwater and brackish water areas. Development of methodological basis for the testing of adaptive capacities (health) of key aquatic organisms provides new knowledge of biological effects of anthropogenic chemical stress in aquatic organisms. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Maintenance of a good quality of surface waters to ensure their ecological safety for human use and the living biota is currently a major issue globally. To achieve this, the development of biological “early warning” technologies for monitoring of aquatic systems exposed to anthropogenic pressures is of high priority. These technologies are highly useful in the early detection of emergency situations (chemical accidents, oil spills, unauthorized dumping of untreated waters, illegal emissions from industry, etc.), which are likely to cause serious hazards for the aquatic environment as well as human populations. In the Gulf of Finland (GoF; northeastern Baltic Sea), high anthropogenic pressures influencing all parts of the marine area impose special requirements for the rapidity of detection and identification of undesirable effects as well as the subsequent decision-making process for the implementation of adequate protection measures to ensure ecological safety of the region. To achieve this, the development and ⁎ Corresponding author. E-mail address: [email protected] (A.N. Sharov).

http://dx.doi.org/10.1016/j.jmarsys.2016.12.005 0924-7963/© 2016 Elsevier B.V. All rights reserved.

implementation of “on-line on-site” methods for the assessment of the ecological status of marine areas is a feasible strategy. One approach to identify changes in the aquatic environment potentially leading to threats to the ecosystem is the assessment of the physiological status of native organisms. Various aquatic species have been used for biomonitoring in different freshwater and marine environments, including the Baltic Sea (e.g., Lehtonen et al., 2014), and their biological responses are commonly accepted to be useful ecological quality indicators. By using biological effect methods it is possible to take into account the cumulative effects of all the influencing factors in an integrative way to reveal and, to some extent, predict any negative changes in habitat water quality. In addition, it is essentially important to apply representatives of local biota for biomonitoring, in this way ensuring “ecological compliance”, i.e., the conditions prevailing in the ecosystem being favourable for the inhabiting biota (Handy and Depledge, 1999). One approach to examine the health of organisms is the use of bioelectronic methods that record physiological parameters. In biosensor systems, the test animals applied are included directly in the system structure as primary converters; thus, they are an integral part of an electronic recording system of certain physiological and behavioural

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parameters reflecting the integrated response of animals to changes in environmental conditions (Depledge et al., 1995; Depledge and Galloway, 2005; Kholodkevich et al., 2008). An essential benefit of biosensor methodologies is the application of rapid, integrated criteria to assess biological effects of contamination and their use in on-line monitoring (Kholodkevich et al., 2011; Kuznetsova and Kholodkevich, 2015). In the GoF, marked gradients in major environmental factors such as salinity and hypoxia determine to a large extent the spatial distribution of fauna, which is often very heterogeneous in the region. Half of the GoF consists of a so-called “critical salinity” zone (Telesh and Khlebovich, 2010) where aquatic organisms of both freshwater and marine origin are found in a weakened physiological state due to the prevailing suboptimal salinity conditions. In the present study, different species in different parts of the GoF were used for the testing of a biosensor system. The freshwater duck mussel (Anodonta anatina) was chosen for the extremely low salinity (0–2, Practical Salinity Scale 1978) eastern GoF, and the Baltic mussel Mytilus trossulus and the Baltic clam Macoma balthica for the more saline waters (5–6) found in the Tallinn Bay (western GoF). All three are key species in their respective habitats. By filtering (M. trossulus) or filtering and deposit feeding (A. anatina and M. balthica) they process large amounts of water and take up particles, and therefore also a large variety of soluble and particle-bound contaminants. At the individual level, the measuring of molecular, cellular, physiological and behavioural responses, the so-called biomarkers, to environmental challenges allows for the assessment of biological effects of contaminants in biota and, to some extent, to predict the sustainability of populations (e.g., Lehtonen et al., 2006). In particular, physiological biomarkers (e.g., characteristics of cardiac activity, respiration, physical activity) are effective tools for bioindication of water quality as they reflect the integrated response of an organism to contamination (Depledge et al., 1995; Hagger et al., 2009; Kholodkevich et al., 2011; Kuznetsova et al., 2010), making possible to obtain information on the ecological status of ecosystems (“ecosystem health”) at the organism level (Depledge and Andersen, 1990; Depledge and Galloway, 2005). During the BEAST project of the Baltic Sea BONUS programme (Lehtonen et al., 2014), a battery of biomarkers were applied in the Baltic Sea, some of them for the first time , (Kholodkevich et al., 2011; Turja et al., 2014). Among these, the time of adaptive heart rate recovery to the background pattern after the introduction and subsequent removal of an additional short-term stress factor (Kholodkevich et al., 2011; Kuznetsova and Kholodkevich, 2015) was applied. Later on, results from the studies above were considered to examine the applicability of the method in the GoF. In this region, regular environmental monitoring has been conducted already for a long period (Telesh et al., 2008; Lips and Lips, 2008; Lips et al., 2014), but, as in most of the Baltic Sea, monitoring of biological effects of contaminants has not been a part of the programme, largely due to the lack of suitable and validated methodologies (Lehtonen et al., 2006, 2014). The present study was carried out in the frame of the trilateral (Estonia, Finland and Russia) “Gulf of Finland Year 2014” research programme, and had the following specific objectives: • to study the applicability of a bioelectronic system for the bioindication of water quality in different areas of the GoF characterized by varying levels and types of anthropogenic pressures; • to select and test local macrozoobenthos species to be used as biosensor organisms using the technology developed; • to study physiological responses of cardiac systems of the selected organisms periodically exposed to additional stress factors. The results of the project were foreseen to promote the development of technologies for the detection and indication of biological effects of pollution globally but also especially concerning the specific characteristics of the GoF ecosystem.

2. Material and methods 2.1. Study sites and sampling The applicability of the method was tested in different areas of the GoF with varying salinity from freshwater in the Neva estuary to brackish water (5–6) in the Tallinn Bay, and using local benthic key species (Fig. 1). In the eastern GoF study area, the experiments were conducted using A. anatina, sampled (n = 16) in the shallow waters of the Kurortny District (Sestroretsk, Dubki Park, Repino, Komarovo) and Peterhof on the eastern shore (Fig. 1B). On the basis of a number of hydrobiological and hydrochemical indicators, the water area around Dubki Park can be considered as a reference site for the Neva Bay estuary whereas the Peterhof area is significantly contaminated by anthropogenic activities (Telesh et al., 2008). Monthly samples (May to September 2014) of 10–16 individual A. anatina of 70–80 mm in length were collected. Within 1–3 h after collecting the mussels were brought to the laboratory in 10 l plastic isothermal containers. In the laboratory, fiber optical sensors of 3 mm in diameter were glued on the shells of the mussels in the area of heart projection. The mussels were then kept in an aquarium with natural water from the sampling site with constant aeration. After a 1–2 h period of stabilization of the heart rate (HR) to the level corresponding to that recorded during active filtering (open shells), the testing of their physiological condition was initiated by a so-called functional load method; in the case of A. anatina this signified the increase of water salinity up to 6 with a subsequent return to the ambient one (Kholodkevich et al., 2015). All the individuals survived the test procedure and were then returned to their natural habitats. M. trossulus and M. balthica were collected from their respective reference sites, the Lahepere Bay and the Naissaar Island (Fig. 1A). One hundred and twenty individuals of M. trossulus were collected by diving from the depth of 3–4 m from a stony substrate. M. balthica (130 individuals) were collected by dredging from the depth of 43 m. Only undamaged individuals were selected for the testing with at least 48 individuals of each species, and the fiber optical sensors were glued on their shells. The collected specimens were transported to the laboratory in isothermal boxes with ambient water. In the laboratory they were kept in tanks in a climate room at 7–10 °C in aerated water collected from their habitats and under a 12 L:12D (light:dark) illumination regime. After testing the cardiac activity baselines for each individual (see below), the bivalves (a total of 48 individuals of each species) were divided into two groups and deployed in cages for 10 weeks at a reference and a contaminated site in the Tallinn Bay region (Fig. 1A). The infaunal species M. balthica were deployed in cages placed in plastic boxes with sediment from the collection site. 2.2. The bioelectronic system for the measuring of cardiac activity in mollusks In 1999, the laser fiber optical photoplethysmograph (Fedotov et al., 2000; Kholodkevich et al., 2008) was developed in the Laboratory of Experimental Ecology of Aquatic Systems of the St. Petersburg Research Center for Ecological Safety of the Russian Academy of Sciences. In 2003–2004, a software was designed to enable real-time estimation of the physiological stress level in benthic invertebrates in the presence of chemical stressors. A limitation to the method is the requirement to use only animals with an external skeleton (crayfish, crabs and shelled mollusks) to which a small sensor (b2 g of weight) can be attached for the registration of cardiac activity (Fedotov et al., 2000; Kholodkevich et al., 2007, 2008). In the papers above it has been demonstrated that the attached sensor does not exert any impacts on normal activities on any of the groups of species tested; animals with a fixed sensor remained in a normal physiological state for several


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Fig. 1. Map of the study sites. A: Tallinn Bay; 1 - Lahepere Bay, 2 - Naissaar Island, 3 - Tallinn Harbour; B: Eastern GoF: 1 – Dubki Park, 2 - Komarovo, 3 – Repino, 4 – Peterhof.

months and showed normal feeding, locomotory activities and behavioural reactions to the introduced stimuli. In addition, their health-related biochemical parameters were shown to remain unaffected by the treatment. The application of the method for the different species of mollusks used in the present study is shown in Fig. 2. The bioelectronic method and hardware allow for the real-time registering and analyzing of the contractile activity of the heart (cardiac activity) of an animal. The method can be used to monitor the HR for several months in ecotoxicological experiments in the laboratory as well as under field conditions.

The experimental set-up for the registration of cardiac activity of bivalves and main stages of data processing are shown in Fig. 3. The infra-red beam of the laser created in a photoplethysmograph (FP) by means of optic-fiber cable reaches the shell of a bivalve, providing radiation of heart area with the diffusion of scattered light. The optical signal reflected from the contractile heart, containing information on alterations of its shape, is returned to the FP. After amplification and filtering in the FP, the analog optical signal (x = f(t)) is transformed into digital form by a 14-bit multichannel analog-to-digital converter. Finally, the signal is transmitted via a USB port to a personal computer for further processing. The purpose-built VarPulse software

Fig. 2. The three bivalve species of the present study, equipped with the fiber optical sensors fixed on their shells for the registration of cardiac activity. A – Anodonta anatina, B - Mytilus trossulus, and C - Macoma balthica. The scale bar corresponds to 1 cm.

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Fig. 3. Installation and automatic processing of cardiac activity of a bivalve. LOFP - laser optical fiber photoplethysmograph; ADC - analog-to-digital converter; PC - personal computer; DF – digital filter; DA – distribution analysis. The main stages of data processing of a sample of cardiac intervals (CI, not b50) are shown: HR - mean HR, SD - standard deviation of HR.

(Kholodkevich et al., 2007, 2008) automatically determines the duration of each cardiac interval and then calculates in real time all the essential characteristics of the photoplethysmogram such as mean HR, standard deviation (SD) of cardiac intervals (CI), and HR variability. The obtained data can also be archived. The software allows for the simultaneous registering and analysis of 7–8 individuals. For example, if two eight-channel installations are used in the experiments, HR of 16 individuals can be measured simultaneously. An example of the installation of a multichannel registration set-up for the measurement of the cardiac activity of a group of animals is shown in Fig. 4. 2.3. Diagnostic of the physiological condition of mollusks using the functional load approach Standardized rapid changes in water salinity (i.e., an increase for freshwater species and a reduction for marine or brackish water ones) or temperature can be used as a so-called functional load to reveal early signals of the deterioration of the health of an organism. To avoid extreme stress to the experimental organisms the changes are applied in the range of the physiological tolerance limits defined for each test species. It has been shown for both marine and freshwater species that individuals collected from clean or less polluted (reference) sites have a higher adaptive capacity compared to those originating from contaminated areas (Kholodkevich et al., 2011). Using the current method this capacity is expressed as a shorter HR recovery time (Trec)

to reach background HR values after the removal of the functional load (Fig. 5; Kholodkevich et al., 2011; Kuznetsova, 2013; Kuznetsova and Kholodkevich, 2015). Furthermore, in comparison with individuals inhabiting contaminated areas, those originating from cleaner environments show higher uniformity in compensatory responses, manifested as a low coefficient of variation of HR (CVHR) typically 0.1–0.3 after the removal of the test stimulus (Kholodkevich et al., 2011). Previous data from the papers above suggest that for freshwater species the optimal range of the water salinity change is an increase of up to 6–7, while for marine or brackish water animals a reduction by 50% from ambient salinity is suitable. This information can be used to standardize the testing procedure for salinity change as a functional load. The previous data also indicate that the duration of the functional load should be 1–2 h after which the water salinity is returned to the initial value by replacement. It has been shown that for different species of benthic invertebrates collected from less polluted habitats the CVHR 1–2 h after removal of the functional load is 5–10% while for those collected from contaminated sites it ranges between 0 and 40% (Turja et al., 2014; Kholodkevich et al., 2011; Kuznetsova and Kholodkevich, 2015). In some cases, the variability indicator CVHR appears to be a better indicator of the influence of chemical stress on the tested animals than Trec of HR itself (Curtis et al., 2000; Kuznetsova and Kholodkevich, 2015), this being related to natural interindividual differences in sensitivity to stress.

Fig. 4. An example of the installation of multichannel registration of the cardiac activity of 16 bivalves, with the interface of the VarPulse software.


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Table 1 Mean Trec and CVHR for A. anatina collected from four sites in the Eastern Gulf of Finland. n = number of individuals. Study site

Trec, min

CVHR

n

Study month

Dubki Komarovo Repino Peterhof

45 ± 11 90 ± 10 120 ± 21 320 ± 17

0.10 0.25 0.30 0.40

64 16 64 16

V–IX VIII V–IX IX

Compared to A. anatina collected from the relatively uncontaminated Kurortny District (sites Dubki Park, Komarovo and Repino), those sampled near Peterhof demonstrated significantly lower Trec (Table 1). Fig. 5. An example of the mean HR trend before (background rate) and during the salinity change, and following the recovery of salinity to the initial value. The time of exposure in the changed salinity is 1 h. 1: mean HR; 2: mean rest HR level; 3: the time interval of HR recovery after the removal of the altered salinity. Arrows indicate the onset of the salinity change (arrow up) and recovery to the ambient salinity (arrow down).

2.4. Data analysis All data from the field samples and caging experiments are expressed as mean ± standard error of mean (SEM) unless stated otherwise. The Trec parameter was calculated as the time (in minutes [min]) between the beginning of the salinity recovery period and the moment when the HR returned to its background level. The same approach was applied to all the study species. Trec was determined for each individual (n = 16 for each group), and mean Trec and SEM were calculated for the group of bivalves from each of the study sites. CVHR was calculated as CVHR = SD/HRmean. Normality and homogeneity of group variances were checked using the ShapiroWilk test (p N 0.05) (Razali and Wah, 2011). Differences among the means were assessed by one-way analysis of variance (ANOVA), and significant differences were defined at p b 0.05 using the Data Analysis ToolPack (MS Excel 2003 for Windows).

3. Results 3.1. A field sampling study in the eastern GoF: A. anatina HR measurements of 16 individuals of A. anatina for each site (total n = 64) from the Kurortny District area (station Dubki Park) in summer 2014 showed a Trec ranging from 40 to 65 min (Fig. 6). A seasonal study from May to September 2014 showed no significant variability in Trec.

3.2. Caging studies in the Tallinn Bay: M. trossulus and M. balthica In M. trossulus, a relatively constant background HR, and a stable dynamic response to salinity change followed by a quick recovery after the removal of the functional load could be observed (Fig. 7). Trec was measured at 35 ± 7 min and CVHR = 0.07, the latter value considered typical for less polluted sites (Kholodkevich et al., 2011; Kuznetsova and Kholodkevich, 2015). Cardiac activity of M. balthica from the less polluted reference site (Naissaar Island; 3 groups of clams with 16 individuals each) showed two different types of HR patterns after exposure to the functional load (Fig. 8). Of the recordings on M. balthica, the first type is similar to the pattern recorded for M. trossulus in the resting state with more or less constant mean HR values. This kind of pattern was observed in 10% of the tested individuals. The second type (90% from observed) is characterized by strongly oscillating features in the HR with an increase followed by a decrease within a period of 1.25–1.5 h. No apparent correspondence of the different cardiac rhythm patterns observed could be related to the size or colour of the clams nor with the activity of their inhalant siphons. Unfortunately, the cages containing M. trossulus in the Tallinn Bay could not be retained and the results are therefore missing. In regard to M. balthica, two examples out of 16 measurements of HR responses after a 10-week exposure near the Tallinn wastewater treatment plant (WWTP) discharge site are presented in Fig. 9. Under the changed salinity some individuals responded by an increased HR while others showed a decrease; however, after a return to the initial salinity all of them recovered their HR pattern to back to the resting level. In M. balthica, the mean Trec before the caging experiment was 55 ± 7 min while after deployment near the WWTP discharge site it increased to 90 ± 20 min (Table 2). The calculation of CVHR failed because of the characteristically irregular fluctuations in HR in this species.

Fig. 6. A. anatina. Seasonal dynamics of the mean recovery time (Trec) after hyper-osmotic functional load testing of specimens from the Eastern GoF in summer 2014. A - Trec measured in mussels collected from Dubki Park (1) and Repino (2); B – Ratio (%) of Trec of mussels from Repino to those collected from Dubki Park, the latter defined as a reference site.

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Fig. 7. Mytilus trossulus. Heart rate in the resting (background) state, under the salinity change (from 5.5 to 3.0) and the following recovery of salinity to the initial value in individuals (n = 8) from the reference site (Lahepere Bay). Duration of hypo-osmotic exposure: 1 h, water temperature: 10 °С.

Fig. 8. Macoma balthica. Two typical HR patterns observed during the testing of individuals collected from the reference site before their deployment in cages to the allegedly polluted target site. Curves 1 and 2: HR trend of two individuals in the resting (background) state, under the salinity change and the following recovery of salinity to the initial value. Dotted curves 3 and 4: time interval of HR recovery (30 and 60 min) of corresponding individuals after the removal of altered salinity. Arrows indicate the onset of the 50% salinity reduction period (arrow down) and recovery to ambient salinity (arrow up).

4. Discussion The present study showed that the bivalves A. anatina, M. trossulus and M. balthica collected from reference sites in the GoF demonstrated

a short time of HR recovery (b60 min), which is in good accordance with previously obtained data for other marine and freshwater mollusks from reference sea areas (Kholodkevich et al., 2011; Turja et al., 2014; Kuznetsova and Kholodkevich, 2015). Compared to their

Fig. 9. Macoma balthica. Two typical HR patterns measured after 10 weeks of exposure near the Tallinn waste water treatment plant discharge area. Curves 1 and 2: HRs trends of two clams before (resting state), under the salinity change, and following the recovery of salinity to the initial value. Dotted curves 3 and 4: the time interval of HR recovery (60 and 90 min) of the corresponding clams after the removal of altered salinity. Arrows indicate the onset of the 50% reduction period in water salinity (arrow down) and recovery to ambient (5.5) salinity (arrow up).

S.V. Kholodkevich et al. / Journal of Marine Systems 171 (2017) 151–158 Table 2 Mean Trec and CVHR for bivalves from the reference sites (Lahepere Bay and Naissaar Island) and after the caging experiment near the Tallinn WWTP discharge area; n = number of individuals. Study site

Bivalves

Trec, min

CVHR

n

Study month

Lahepere Bay Naissaar Island Tallinn WWTP discharge area

M. trossulus M. balthica M. balthica

35 ± 7 55 ± 7 90 ± 20

0.07 – –

48 48 16

VI VII, VIII X

157

4. Further development of operational technologies to perform the method under field conditions. 5. Studies on effects of different physiological stages of test organisms, such as a pre-spawning state and spawning, and also possible physiological variability between individuals on cardiac activity parameters.

5. Conclusions respective reference sites, individuals of all three species collected from or transplanted to sites with high anthropogenic pressure demonstrated a markedly prolonged Trec, extending up to several hours. The increase in Trec is very likely associated with the deterioration of the physiological status of the organisms due to reduced environmental quality. Chronic water pollution is well-known to be reflected in the level of adaptive capacities of local aquatic organisms. Corroborating this, the present study demonstrates that using the bioelectronic cardiac activity measurement method the deleterious effects of pollution can be detected in animals residing permanently in chronically polluted sites as well as in those transplanted to contaminated sites for a couple of months. Mussel caging has been successfully used to assess environmental stress in coastal environments in many seas areas (e.g., Regoli et al., 2004; Serafim et al., 2011; Turja et al., 2013). So far, very few studies dealing with the biological effects of WWTP effluents on macroinvertebrates can be found. In the GoF, Turja et al. (2015) carried out a onemonth caging study on M. trossulus at sites 0.8 and 1.1 km from the Helsinki WWTP discharge site with a reference site 4 km away. Significant antioxidant, genotoxic and lysosomal responses were observed closer to the WWTP discharge area, coinciding with elevated levels of some contaminants (e.g., pharmaceuticals). Similar to the present study, it is difficult to assess if the negative effects observed were due to the WWTP efflux or other pollution present in the study area under various anthropogenic pressures. M. balthica has been used as an indicator organism in the assessment of marine pollution and in biomarker responses studies in the Baltic Sea (Lehtonen et al., 2006; Putna et al., 2014). However, no studies are available on the monitoring of cardiac activity in this species. The small size of M. balthica complicates cardiac activity monitoring since compared to larger species it is difficult to fix sensors on their shells. In the present study, a marked variability in cardiac response patterns in M. balthica was recorded even without a functional load. Compared to mussels, physiological responses of M. balthica to environmental stressors have been investigated to a lesser extent; therefore, the reasons for the observed differences remain a target for further studies. For example, information is needed on the possible links of cardiac activity with filtration activity and general metabolism in this species. This study has shown, the bioelectronic cardiac monitoring system can be used to detect effects of deteriorated environmental conditions in various bivalve species. Its applicability has been shown in the GoF, an area characterized by an ecologically significant salinity gradient. For further development, the successful application of this method in monitoring and assessment of pollution and water quality especially in this region requires the following actions: 1. Selection of the most available benthic invertebrates inhabiting the GoF that is suitable for use as test organisms in bioelectronic systems. 2. Determination of distribution and limits of stress tolerance of the species of freshwater or marine origin to establish the limits of their use as test organisms in different sub-regions of the GoF. 3. Mapping of the distribution of the selected bioindicator organisms to establish the limits of their physiological ranges and adaptive capacities in ecologically different habitats to be used in the standardized tests.

Application of the bioelectronic system described in this study and data treatment methods based on it are useful tools in the biomonitoring of freshwater and brackish water areas of the GoF. Development of the methodological basis for testing adaptive capacities related to the health of key aquatic organisms provides new insights into biological effects of anthropogenic chemical stress on aquatic organisms. It also provides a useful indication of ecosystem health in general where the state of the biota is a significant component. The study shows that the selected mollusks (M. trossulus, M. balthica and A. anatina) are suitable to be used in the bioelectronic test system. It also identifies gaps in our knowledge of the cardiac system functioning in different species commonly used as environmental bioindicators. The study calls for a more comprehensive analysis of physiological responses especially in M. balthica as an indicator species in the Baltic Sea. The approach of measuring biological effects in bivalves deployed in cages in contaminated target areas was successfully combined with the application of the bioelectronic cardiac activity method to detect and the decline in the adaptive capacity of the organisms. Development of the these methods for efficient diagnostics of pollution impact in the aquatic environment, taking into account the specific characteristics of different regions such as the GoF, are foreseen to increase the reliability and cost-efficiency environmental monitoring and status assessments. Acknowledgements The work was carried out with partial use of equipment of St. Petersburg State University Research Park resource center Environmental Safety Observatory. References Curtis, T.M., Williamson, R., Depledge, M.H., 2000. Simultaneous, long-term monitoring of valve and cardiac activity in the blue mussel Mytilus edulis exposed to copper. Mar. Biol. 136, 837–846. Depledge, M.H., Andersen, B.B., 1990. A computer-aided physiological monitoring system for continuous, long-term recording of cardiac activity in selected invertebrates. Comp. Biochem. Physiol. 96 (4), 473–477. Depledge, M.H., Galloway, T.S., 2005. Healthy animals, healthy ecosystems. Front. Ecol. Environ. 3 (5), 251–258. Depledge, M.H., Aagaard, A., Györkös, P., 1995. Assessment of trace metal toxicity using molecular, physiological and behavioral biomarkers. Mar. Pollut. Bull. 31, 19–27. Fedotov, V.P., Kholodkevich, S.V., Strochilo, A.G., 2000. Study of contractile activity of the crayfish heart with the aid of a new non-invasive technique. J. Evol. Biochem. Physiol. 36 (3), 288–293. Hagger, J.A., Galloway, T.S., Langston, W.J., Jones, M.B., 2009. Application of biomarkers to assess the condition of European saltwater sites. Environ. Pollut. 157, 2003–2010. Handy, R.D., Depledge, M.H., 1999. Physiological responses: their measurement and use as environmental biomarkers in ecotoxicology. Ecotoxicology 8, 329–349. Kholodkevich, S.V., Fedotov, V.P., Ivanov, A.V., Kuznetsova, T.V., Kurakin, A.S., Kornienko, E.L., 2007. Fiber-Optical Remote Biosensor Systems for Permanent Biological Monitoring of the Surface Waters Quality and Bottom Sediments in the Real Time. (http://www.ices.dk/sites/pub/CM Doccuments/CM-2007/I/I1507.pdf). Kholodkevich, S.V., Ivanov, A.V., Kurakin, A.S., Kornienko, E.L., Fedotov, V.P., 2008. Real time biomonitoring of surface water toxicity level at water supply stations. J. Environ. Bioindic. 3 (1), 23–34. Kholodkevich, S.V., Kuznetsova, T.V., Lehtonen, K.K., Kurakin, A.S., 2011. Experiences on ecological status assessment of the Gulf of Bothnia different sites based on cardiac activity biomarkers of caged mussels (Mytilus edulis). ICES Annual Science Conference, Gdansk, Poland (http://www.ices.dk/products/CMdocs/CM-2011/R/R2011.pdf). Kholodkevich, S., Sharov, A., Nikolić, M., Joksimović, A., 2015. Bioindication of aquatic ecosystems on the base of the assessment of functional state of freshwater bivalve mollusks biomarkers. Proceedings 4th Mediterranean Conference on Embedded Computing, MECO. IEEE conference publications, Budva, Montenegro, pp. 345–348.

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